Replication data for: Learning about Risk and Return: A Simple Model of Bubbles and Crashes
Principal Investigator(s): View help for Principal Investigator(s) William A. Branch; George W. Evans
Version: View help for Version V1
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matlab_vetted | 10/25/2021 01:51:PM | ||
LICENSE.txt | text/plain | 14.6 KB | 10/12/2019 05:12:PM |
Project Citation:
Branch, William A., and Evans, George W. Replication data for: Learning about Risk and Return: A Simple Model of Bubbles and Crashes. Nashville, TN: American Economic Association [publisher], 2011. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2019-10-12. https://doi.org/10.3886/E114223V1
Project Description
Summary:
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This paper demonstrates that an asset pricing model with least-squares
learning can lead to bubbles and crashes as endogenous responses to the fundamentals driving asset prices. When agents are risk-averse they need to make forecasts of the conditional variance of a stock's return. Recursive updating of both the conditional variance and the expected return implies several mechanisms through which
learning impacts stock prices. Extended periods of excess volatility, bubbles, and crashes arise with a frequency that depends on the extent to which past data is discounted. A central role is played by changes over time in agents' estimates of risk. (JEL D81, D83, E32,
G01, G12)
Scope of Project
Subject Terms:
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asset-pricing;
bubbles;
adaptive learning
JEL Classification:
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D81 Criteria for Decision-Making under Risk and Uncertainty
D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
E32 Business Fluctuations; Cycles
G01 Financial Crises
G12 Asset Pricing; Trading Volume; Bond Interest Rates
D81 Criteria for Decision-Making under Risk and Uncertainty
D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
E32 Business Fluctuations; Cycles
G01 Financial Crises
G12 Asset Pricing; Trading Volume; Bond Interest Rates
Data Type(s):
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program source code
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